Kriem Lukas Simon, Wright Kevin, Ccahuana-Vasquez Renzo Alberto, Rupp Steffen
Fraunhofer Institute for Interfacial Engineering and Biotechnology, Stuttgart, Germany.
Procter & Gamble, Reading, United Kingdom.
Front Microbiol. 2021 Oct 5;12:729720. doi: 10.3389/fmicb.2021.729720. eCollection 2021.
Techniques for continuously monitoring the formation of subgingival biofilm, in relation to the determination of species and their accumulation over time in gingivitis and periodontitis, are limited. In recent years, advancements in the field of optical spectroscopic techniques have provided an alternative for analyzing three-dimensional microbiological structures, replacing the traditional destructive or biofilm staining techniques. In this work, we have demonstrated that the use of confocal Raman spectroscopy coupled with multivariate analysis provides an approach to spatially differentiate bacteria in an model simulating a subgingival dual-species biofilm. The present study establishes a workflow to evaluate and differentiate bacterial species in a dual-species biofilm model, using confocal Raman microscopy (CRM). Biofilm models of and were cultured using the "Zürich model" and were analyzed using CRM. Cluster analysis was used to spatially differentiate and map the biofilm model over a specified area. To confirm the clustering of species in the cultured biofilm, confocal laser scanning microscopy (CLSM) was coupled with fluorescent hybridization (FISH). Additionally, dense bacteria interface area (DBIA) samples, as an imitation of the clusters in a biofilm, were used to test the developed multivariate differentiation model. This confirmed model was successfully used to differentiate species in a dual-species biofilm and is comparable to morphology. The results show that the developed workflow was able to identify main clusters of bacteria based on spectral "fingerprint region" information from CRM. Using this workflow, we have demonstrated that CRM can spatially analyze two-species biofilms, therefore providing an alternative technique to map oral multi-species biofilm models.
与牙龈炎和牙周炎中物种的确定及其随时间的积累相关的连续监测龈下生物膜形成的技术有限。近年来，光学光谱技术领域的进展为分析三维微生物结构提供了一种替代方法，取代了传统的破坏性或生物膜染色技术。在这项工作中，我们证明了使用共焦拉曼光谱结合多变量分析为在模拟龈下双物种生物膜的模型中对细菌进行空间区分提供了一种方法。本研究建立了一个工作流程，使用共焦拉曼显微镜（CRM）来评估和区分双物种生物膜模型中的细菌物种。使用“苏黎世模型”培养变形链球菌和牙龈卟啉单胞菌的生物膜模型，并使用CRM进行分析。聚类分析用于在指定区域对生物膜模型进行空间区分和绘图。为了确认培养生物膜中物种的聚类，将共焦激光扫描显微镜（CLSM）与荧光原位杂交（FISH）相结合。此外，作为生物膜中聚类的模拟，密集细菌界面区域（DBIA）样本被用于测试所开发的多变量区分模型。这个经过验证的模型成功地用于区分双物种生物膜中的物种，并且与形态学相当。结果表明，所开发的工作流程能够根据CRM的光谱“指纹区域”信息识别细菌的主要聚类。使用这个工作流程，我们证明了CRM可以对双物种生物膜进行空间分析，因此提供了一种绘制口腔多物种生物膜模型的替代技术。
